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Microfacies Analysis and Basin Development of Hartha Formation in East Baghdad Oil field, Central Iraq
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The Hartha Formation is one of the important formations deposited during Late Campanian age.

The present study deals with four boreholes (EB-53, 54, 55 and 56) within the East Baghdad oil field to diagnoses the microfacies and interpret the depositional environments.

Six major microfacies were recognized in the succession of the Hartha Formation. Their characteristic grain types and depositional texture enabled the recognition of paleoenvironment. There are Orbitoides  wackestone-packstone , Orbitoides - miliolid wackestone, Peloidal and Pellets - echinoderm wackestone to packstone, Peloidal wackestone to packstone, Pelletal wackestone to packstone, and Planktonic foraminifera wackestone-packstone.

Four associations’ facies were recognized in this succession, which are shallow open marine, deep open marine, semi-resricted, and restricted. The distribution of these associations led to the recognition of three major depositional stages in the studied succession.

The first stage is represented by the semi-restricted facies within the lower part of the Hartha Formation, which is characterized by Orbitoides - miliolid wackestone to the northwest direction and developed to shallow open marine and deep marine to the southeast direction. In the second stage, the sea level was rising to deposit the deep open marine facies represented by planktonic foraminifera wackestone-packstone microfacies above the semi-restricted facies ,where the succession became characterized by Peloidal and Pellets - echinoderm wackestone to packstone microfacies of restricted association. The third stage is represented by the continuation of sea level rise. This caused the building of carbonate ramp of Shiranish Formation above the shallow open marine of Hartha Formation with conformable surface.

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Publication Date
Tue Mar 08 2022
Journal Name
Multimedia Tools And Applications
Comparison study on the performance of the multi classifiers with hybrid optimal features selection method for medical data diagnosis
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Publication Date
Fri Apr 26 2019
Journal Name
Journal Of Contemporary Medical Sciences
Breast Cancer Decisive Parameters for Iraqi Women via Data Mining Techniques
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Objective This research investigates Breast Cancer real data for Iraqi women, these data are acquired manually from several Iraqi Hospitals of early detection for Breast Cancer. Data mining techniques are used to discover the hidden knowledge, unexpected patterns, and new rules from the dataset, which implies a large number of attributes. Methods Data mining techniques manipulate the redundant or simply irrelevant attributes to discover interesting patterns. However, the dataset is processed via Weka (The Waikato Environment for Knowledge Analysis) platform. The OneR technique is used as a machine learning classifier to evaluate the attribute worthy according to the class value. Results The evaluation is performed using

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Publication Date
Sat Sep 30 2023
Journal Name
Iraqi Journal Of Science
Efficient Approximate Analytical Methods to Solve Some Partial Differential Equations
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     The goal of this research is to solve several one-dimensional partial differential equations in linear and nonlinear forms using a powerful approximate analytical approach. Many of these equations are difficult to find the exact solutions due to their governing equations. Therefore, examining and analyzing efficient approximate analytical approaches to treat these problems are required. In this work, the homotopy analysis method (HAM) is proposed. We use convergence control parameters to optimize the approximate solution. This method relay on choosing with complete freedom an auxiliary function linear operator and initial guess to generate the series solution. Moreover, the method gives a convenient way to guarantee the converge

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Publication Date
Sat Dec 02 2017
Journal Name
Al-khwarizmi Engineering Journal
Direction Finding Using GHA Neural Networks
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 This paper adapted the neural network for the estimating of the direction of arrival (DOA). It uses an unsupervised adaptive neural network with GHA algorithm to extract the principal components that in turn, are used by Capon method to estimate the DOA, where by the PCA neural network we take signal subspace only and use it in Capon (i.e. we will ignore the noise subspace, and take the signal subspace only).

 

 

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Publication Date
Tue Mar 04 2008
Journal Name
Journal Of Baghdad College Of Dentistry
Twelve months clinical comparison between modified Widman flap with or without enamel matrix derivative for the treatment of infrabony defects
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Publication Date
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Journal Name
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Determining standard levels to test the strength endurance characteristic of speed for basketball players for juniors aged under (16) years
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Publication Date
Fri May 19 2017
Journal Name
International Journal Of Environment, Agriculture And Biotechnology 2 (4 …‏
Effect of Knives Type on Some Operational Characteristics fora Locally Assembly Motorized Vibration Cutter Used for Date Palm Fronds Pruning‏
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Publication Date
Thu Oct 25 2018
Journal Name
Al-nahrain Journal Of Science
Synthesis of some New 3-Substituted Heterocyclic Compounds Containing Bridgehead Nitrogen from 2-Amino Pyridine with Study Their Biological Activity
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